Metrics question
Say you're the PM of Facebook and you have launched a new feature X with 20% engagement. How will you know if the overall engagement of Facebook has increased/decreased or remained same?
- Meta
- Metrics
- Medium
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What this question tests
Metrics tradeoff reasoning: can you distinguish a feature-level metric from platform-level impact, including cannibalization and displacement effects.
How to approach it
- Clarify what 'engagement' means at the platform level: total time spent, DAU/MAU, or a composite quality-adjusted engagement score.
- Recognize the core risk: feature X's 20% engagement could be entirely cannibalized from other Facebook activities, not incremental to the platform.
- Propose an experiment design: compare total platform engagement between a test group with feature X and a holdout group without it, not just feature X's own engagement number.
- Watch for displacement: if users spend more time on feature X but less elsewhere, net platform time may be flat or down even though X 'succeeded'.
- Segment by user type: feature X might help some segments (new users finding value) while cannibalizing others (existing heavy users just shifting behavior).
- Define the decision: only call it a platform win if the holdout comparison shows net-positive total engagement, not feature X's isolated number.
What a strong answer includes
- Immediately identifies cannibalization/displacement as the central risk, rather than accepting feature X's 20% at face value.
- Proposes the correct experimental design, holdout group comparing total platform engagement, not just before/after on feature X.
- Distinguishes incremental value from shifted value with a clear example (new users vs existing heavy users).
- States an explicit decision rule based on net platform impact, not feature-level metrics alone.
Common mistakes
- Accepting feature X's 20% engagement figure as proof of overall platform growth without checking cannibalization.
- Not proposing a holdout/control group design to isolate incremental versus displaced engagement.
Likely follow-up questions
- How would you design the holdout group so it's not contaminated by network effects (friends using feature X)?
- What would you tell the team if the net platform engagement turned out flat?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 2: Data fluency: SQL, logs, and reading the truth yourself
- Chapter 14: Get the job: the AI PM interview loop